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<table width="100%" summary="page for politicalKnowledge"><tr><td>politicalKnowledge</td><td style="text-align: right;">R Documentation</td></tr></table>

<h2> 
Political knowledge in the US and Europe 
</h2>

<h3>Description</h3>

<p>Data from McChesney and Nichols (2010) on domestic and international 
knowledge in Denmark, Finland, the UK and the US among college 
graduates, people with some college, and roughly 12th grade only.  
</p>


<h3>Usage</h3>

<pre>
data(politicalKnowledge)
</pre>


<h3>Format</h3>

<p>A <code>data.frame</code> containing 12 columns and 4 rows.
</p>

<dl>
<dt>country</dt><dd>
<p>a character vector of Denmark, Finland, UK, and 
US, being the four countries comparied in this data set.  
</p>
</dd>
<dt>DomesticKnowledge.hs, DomesticKnowledge.sc, 
DomesticKnowledge.c</dt><dd>
<p>percent correct answers to calibrated questions regarding 
knowledge of prominent items in domestic news in a 
survey of residents of the four countries among college 
graduates (ending &quot;.c&quot;), some college (&quot;.sc&quot;) and 
high school (&quot;hs&quot;).  Source:  McChesney and Nichols
(2010, chapter 1, chart 8).  
</p>
</dd>
<dt>InternationalKnowledge.hs, InternationalKnowledge.sc, 
InternationalKnowledge.c</dt><dd>
<p>percent correct answers to calibrated questions regarding
knowledge of prominent items in international news in a 
survey of residents of the four countries by education 
level as for DomesticKnowledge.  Source:  McChesney and 
Nichols (2010, chapter 1, chart 7).  
</p>
</dd>
<dt>PoliticalKnowledge.hs, PoliticalKnowledge.sc, 
PoliticalKnowledge.c</dt><dd>
<p>average of domestic and international knowledge
</p>
</dd>
<dt>PublicMediaPerCapita</dt><dd>
<p>Per capital spending on public media in 2007 
in US dollars from McChesney and Nichols (2010, 
chapter 4, chart 1)
</p>
</dd>
<dt>PublicMediaRel2US</dt><dd>
<p>Spending on public media relative to the US, being 
<code>PublicMediaPerCapita / PublicMediaPerCapita[4]</code>.  
</p>
</dd>
</dl>



<h3>Author(s)</h3>

<p>Spencer Graves</p>


<h3>Source</h3>

<p>Robert W. McChesney and John Nichols (2010) <em>The Death and 
Life of American Journalism</em> (Nation Books)
</p>


<h3>Examples</h3>

<pre>
##
## 1. Combine first 2 rows 
##
data(politicalKnowledge)
pk &lt;- politicalKnowledge[-1,]
pk[1, -1] &lt;- ((politicalKnowledge[1, -1] + 
                 politicalKnowledge[2, -1])/2)
pk[1, 'country'] &lt;- 'DK-FI'

##
## 2.  plot
##
xlim &lt;- range(pk[, 'PublicMediaPerCapita'])
ylim &lt;- 100*range(pk[2:7])
text.cex &lt;- 2

# to label the lines 
(US.UK &lt;- (pk[2, -1]+pk[3, -1])/2)

#png('Knowledge v. public media.png')
op &lt;- par(mar=c(5, 7, 4, 2)+.1)
plot(c(0, 110), 100*ylim, type='n', axes=FALSE,
     xlab='public media $ per capita',
     ylab='Political Knowledge\n(% of standard questions)',
     cex.lab=2)
axis(1, cex.axis=2)
axis(2, las=2, cex.axis=2)
with(pk, text(PublicMediaPerCapita, 100*PoliticalKnowledge.hs,
              country, cex=text.cex, xpd=NA, 
              col=c('forestgreen', 'orange', 'red')))
with(pk, text(PublicMediaPerCapita, 100*PoliticalKnowledge.sc,
              country, cex=text.cex, xpd=NA, 
              col=c('forestgreen', 'orange', 'red')))
with(pk, text(PublicMediaPerCapita, 100*PoliticalKnowledge.c,
              country, cex=text.cex, xpd=NA, 
              col=c('forestgreen', 'orange', 'red')))
with(pk, lines(PublicMediaPerCapita, 100*PoliticalKnowledge.hs,
               type='b', pch=' '))
with(pk, lines(PublicMediaPerCapita, 100*PoliticalKnowledge.sc,
               type='b', pch=' '))
with(pk, lines(PublicMediaPerCapita, 100*PoliticalKnowledge.c,
               type='b', pch=' '))
with(US.UK, text(PublicMediaPerCapita, 100*PoliticalKnowledge.hs,
                 'High School\nor less', srt=37, cex=1.5))
with(US.UK, text(PublicMediaPerCapita, 100*PoliticalKnowledge.sc,
                 'some\ncollege', srt=10.5, cex=1.5))
with(US.UK, text(PublicMediaPerCapita, 100*PoliticalKnowledge.c,
                 "Bachelor's\nor more", srt=-1, cex=1.5))

par(op)
#dev.off()

##
## redo for Wikimedia commons
## without English axis labels 
## to facilitate multilingual use 
##
#svg('Knowledge v. public media.svg')
op &lt;- par(mar=c(3,3,2,2)+.1)
plot(c(0, 110), 100*ylim, type='n', axes=FALSE,
     xlab='', ylab='', cex.lab=2)
axis(1, cex.axis=2)
axis(2, las=2, cex.axis=2)
with(pk, text(PublicMediaPerCapita, 100*PoliticalKnowledge.hs,
              country, cex=text.cex, xpd=NA, 
              col=c('forestgreen', 'orange', 'red')))
with(pk, text(PublicMediaPerCapita, 100*PoliticalKnowledge.sc,
              country, cex=text.cex, xpd=NA, 
              col=c('forestgreen', 'orange', 'red')))
with(pk, text(PublicMediaPerCapita, 100*PoliticalKnowledge.c,
              country, cex=text.cex, xpd=NA, 
              col=c('forestgreen', 'orange', 'red')))
with(pk, lines(PublicMediaPerCapita, 100*PoliticalKnowledge.hs,
               type='b', pch=' '))
with(pk, lines(PublicMediaPerCapita, 100*PoliticalKnowledge.sc,
               type='b', pch=' '))
with(pk, lines(PublicMediaPerCapita, 100*PoliticalKnowledge.c,
               type='b', pch=' '))
par(op)
#dev.off()

</pre>


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